Gene Correlation Network Analysis to Identify Biomarkers of Peri-Implantitis.

ABSTRACT: Background and Objectives: The histopathological and clinical conditions for transforming peri-implant mucositis into peri-implantitis (PI) are not fully clarified. We aim to uncover molecular mechanisms and new potential biomarkers of PI. Materials and Methods: Raw GSE33774 and GSE57631 datasets were obtained from the Gene Expression Omnibus (GEO) database. The linear models for microarray data (LIMMA) package in R software completes differentially expressed genes (DEGs). We conducted a weighted gene co-expression network analysis (WGCNA) on the top 25% of altered genes and identified the key modules associated with the clinical features of PI. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the R softwar

SUBMITTER: Sun B 

PROVIDER: S-EPMC9416455 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature